[{"data":1,"prerenderedAt":138},["ShallowReactive",2],{"page-\u002Fen\u002Fservices\u002Fcompany-ai-os":3},{"id":4,"title":5,"body":6,"description":129,"extension":130,"meta":131,"navigation":132,"og":133,"path":134,"seo":135,"service":133,"stem":136,"__hash__":137},"pages\u002Fen\u002Fservices\u002Fcompany-ai-os.md","Company AI OS",{"type":7,"value":8,"toc":125},"minimark",[9,19,27,36,45,53,60,72,80,91,99,107,114,120],[10,11],"page-head",{":crumbs":12,":cta":13,":facts":14,":shot":15,"eyebrow":16,"lead":17,"title":18},"[{\"label\":\"Home\",\"to\":\"\u002F\"},{\"label\":\"Services\"},{\"label\":\"Company AI OS\"}]","{\"to\":\"#contact\",\"label\":\"Book a 30-minute call\"}","[{\"icon\":\"layers\",\"text\":\"Unified AI workspace\"},{\"icon\":\"plug\",\"text\":\"Secure connections\"},{\"icon\":\"database\",\"text\":\"Shared knowledge\"},{\"icon\":\"shield-check\",\"text\":\"Governance and control\"}]","{\"src\":\"\u002Fassets\u002Fimg\u002Fcompany-ai-os-hero.jpg\",\"alt\":\"Company AI OS workspace: a catalogue of approved assistants, agents and workflows on the left, a company assistant chat in the center, and review queue, AI spend limits and connected sources on the right.\"}","For companies ready to scale AI","Connect your team, tools and company knowledge in one AI platform. Run agentic workflows with clear controls, reuse approved learning and measure results. Your data, context and custom workflows remain yours.","One AI platform for your team, knowledge and agentic workflows.",[20,21],"stat-grid",{":stats":22,"eyebrow":23,"index":24,"lead":25,"title":26},"[{\"value\":\"44%\",\"label\":\"of organizations are scaling AI company-wide — McKinsey\",\"Aug 2026\":null},{\"value\":\"14%\",\"label\":\"of small businesses have AI fully embedded in core operations — Goldman Sachs\"},{\"value\":\"49%\",\"label\":\"of SMB leaders cite data privacy and security as an adoption concern — Upwork\"}]","When tools are many, and the system is none","01","AI adoption and productivity keep growing — but integration and trust remain the blockers. The more teams use AI, the more shared knowledge, clear rules and reliable processes matter.","AI success creates a new bottleneck.",[28,29],"editorial-list",{":rows":30,"clarity":31,"eyebrow":32,"index":33,"lead":34,"title":35},"[{\"title\":\"Repeated setup, repeated corrections\",\"text\":\"Each new workflow rebuilds the same connections and repeats earlier corrections. New processes need more setup and rework every time.\"},{\"title\":\"AI expands faster than control\",\"text\":\"Owners, access rules, approvals and budgets differ across tools — leadership struggles to control access, actions and spending.\"},{\"title\":\"AI uses inconsistent company knowledge\",\"text\":\"Separate copies of SOPs, client details and rules drift out of date. Conflicting answers create rework and weaken trust.\"},{\"title\":\"Company AI depends on individuals\",\"text\":\"Prompts, context and workflows sit in personal accounts. Work becomes harder to share, maintain or hand over.\"},{\"title\":\"More AI, unclear business value\",\"text\":\"Usage grows, but time saved, quality and total cost are not tracked — so nobody can see what to expand, improve or stop.\"}]","Company AI OS gives these efforts a shared foundation for access, knowledge, control and improvement.","The standalone AI ceiling","02","When AI tools grow separately, every new workflow repeats the setup — and leadership loses the view.","Signs your company is outgrowing standalone AI.",[37,38],"split-list",{":even":39,":list":40,":middle":39,"eyebrow":41,"index":42,"lead":43,"title":44},"true","[\"\u003Cstrong>It is\u003C\u002Fstrong> one workspace where your team finds and uses approved company AI\",\"\u003Cstrong>It is\u003C\u002Fstrong> a shared context layer: company knowledge, within each user's permissions\",\"\u003Cstrong>It is\u003C\u002Fstrong> an engine that runs business processes across AI, people and tools\",\"\u003Cstrong>It is\u003C\u002Fstrong> governance: owners, access rules, approvals and budgets in one place\",\"\u003Cstrong>It is not\u003C\u002Fstrong> a product you buy off the shelf — it is tailored to your processes and stack\",\"\u003Cstrong>It is not\u003C\u002Fstrong> a replacement for your existing software — it connects and improves what your team already uses\",\"\u003Cstrong>It does not\u003C\u002Fstrong> retrain models — learning is saved as approved, versioned, owner-controlled knowledge\",\"\u003Cstrong>It is not\u003C\u002Fstrong> a lock-in: your data, context and custom workflows remain yours\"]","What it is — and is not","03","An operating layer for company AI — not another tool subscription.","What Company AI OS is. And what it is not.",[46,47],"os-stack",{":layers":48,"eyebrow":49,"index":50,"lead":51,"title":52},"[{\"n\":\"1\",\"title\":\"Unified Company AI Workspace\",\"text\":\"One place to find approved company AI, start work and review results — assistants, agents, workflows, dashboards — with role-based access.\",\"tags\":[\"Assistants\",\"Agents & skills\",\"Workflows\",\"Dashboards\"]},{\"n\":\"2\",\"title\":\"Shared Company Context\",\"text\":\"Documents, SOPs, CRM, project tools and client knowledge connected into one context, used within access rules and with source references.\",\"tags\":[\"Documents\",\"CRM\",\"Client knowledge\",\"Source priorities\"]},{\"n\":\"3\",\"title\":\"Agentic Workflows Engine\",\"text\":\"Business processes run across AI, people and tools: reusable agents, schedules and triggers, human review where needed, recovery when interrupted.\",\"tags\":[\"Reusable agents\",\"Human review\",\"Recovery\"]},{\"n\":\"4\",\"title\":\"AI Governance & Control\",\"text\":\"Complete AI inventory, named owners, permissions, approval steps, model routing, budgets, audit trail, versions and an emergency stop.\",\"tags\":[\"Ownership\",\"Permissions\",\"Budgets\",\"Audit trail\"]},{\"n\":\"5\",\"title\":\"Organizational Memory & Learning\",\"text\":\"Approved decisions, corrections and client preferences are saved, owner-reviewed and versioned — then applied to relevant future work.\",\"tags\":[\"Decisions\",\"Corrections\",\"Preferences\",\"Versioned\"]},{\"n\":\"6\",\"title\":\"AI Performance & Optimization\",\"text\":\"Quality, accuracy, correction rates, latency, cost per task, adoption and business KPIs — baseline before the build, monthly reporting after.\",\"tags\":[\"Quality\",\"Cost per task\",\"Business KPI\",\"Regression testing\"]}]","How it is built","04","One platform covering how people work with AI, how company AI gets work done, and how it improves over time.","Six core capabilities, one coherent system.",[54,55],"media-figure",{"alt":56,"caption":57,"ratio":58,"src":59},"Company AI OS workspace: assistants, agents and agentic workflows in a catalogue on the left, a working chat in the center, and AI spend, usage and limits on the right.","The unified workspace: find approved company AI, start work and review results — with role-based access, spend limits and business dashboards.","1672\u002F941","\u002Fassets\u002Fimg\u002Fcompany-ai-os-hero.jpg",[61,62],"context-flow",{":center":63,":chips":64,":outputs":65,":sources":66,"caption":67,"eyebrow":68,"index":69,"lead":70,"title":71},"{\"icon\":\"database\",\"label\":\"Shared Company Context\"}","[\"Knowledge Assistant\",\"Reusable connections\",\"Access follows permissions\",\"Updated company knowledge\",\"Clear source priorities\"]","[{\"icon\":\"presentation\",\"label\":\"Client reporting\"},{\"icon\":\"file-text\",\"label\":\"Proposal drafting\"},{\"icon\":\"user\",\"label\":\"Onboarding\"},{\"icon\":\"activity\",\"label\":\"Campaign analysis\"},{\"icon\":\"message\",\"label\":\"Answers with source references\"}]","[{\"icon\":\"file-text\",\"label\":\"Documents and SOPs\"},{\"icon\":\"users\",\"label\":\"CRM\"},{\"icon\":\"grid\",\"label\":\"Asana\"},{\"icon\":\"book\",\"label\":\"Notion\"},{\"icon\":\"database\",\"label\":\"Databases\"},{\"icon\":\"heart\",\"label\":\"Client knowledge\"}]","Representative connection set — sources and use cases are scoped to your stack.","Core capability 2 · Shared Company Context","06","Company documents, tools and client knowledge flow into one shared context — and every AI capability draws from it, within each user''s permissions and with clear source priorities.","Connected once. Used everywhere.",[73,74],"numbered-cards",{":items":75,"eyebrow":76,"index":77,"lead":78,"title":79},"[{\"title\":\"Capacity\",\"text\":\"Less time finding information and tools. Fewer manual handoffs. Time from request to completion, and processes completed per week, become visible and improvable.\"},{\"title\":\"Quality\",\"text\":\"Fewer errors from outdated information. More outputs meeting company standards. Repeated corrections on comparable work drop as approved learning is reused.\"},{\"title\":\"Cost\",\"text\":\"Total cost per completed task, model and tool usage, human review time, and spend on unused or duplicate AI — one view instead of scattered invoices.\"},{\"title\":\"Risk\",\"text\":\"Every process with a named owner. Actions with required approvals. Access or policy violations, budget breaches and time-to-stop-a-process all measured.\"}]","What the business gets","07","We agree the measures that matter to your business, record the starting point before the build, and track progress from month one.","Measured across capacity, quality, cost and risk.",[81,82],"statcards",{":cta":83,":split":39,":stats":84,"disclaimer":85,"eyebrow":86,"intro":87,"title":88,"chart":89,"index":90},"{\"to\":\"\u002Fcase-studies\u002Fcurve-ai-business-scan\",\"label\":\"Read the Curve case study\"}","[{\"value\":\"Reuse\",\"label\":\"integrations\",\"context\":null,\"permissions and evaluation framework\":null,\"note\":\"Shared setup carries over to every new workflow.\"},{\"value\":\"Faster\",\"label\":\"launches from existing agents and templates\",\"note\":\"Start from what already works instead of from zero.\"},{\"value\":\"Central\",\"label\":\"maintenance of shared components\",\"note\":\"Fix once, test the impact on each process.\"},{\"value\":\"1×\",\"label\":\"the shared setup is paid once\",\"note\":\"New workflow cost = process setup + genuinely new requirements.\"}]","Illustrative build-cost structure, not a forecast. Platform and usage costs continue; reuse depends on scope.","The economics of reuse","The AI OS Foundation creates a shared starting point — integrations, context, permissions, testing and monitoring. Every later workflow reuses it, so new work is scoped only to what is genuinely new.","Each new workflow costs less than the last.","reuse","08",[81,92],{":cta":93,":split":39,":stats":94,"disclaimer":95,"eyebrow":96,"intro":97,"title":98,":ink":39},"{\"to\":\"\u002Fcase-studies\u002Fcurve-ai-business-scan\",\"label\":\"Read the Curve Case Study\"}","[{\"value\":\"$241K\",\"label\":\"potential annual value identified\",\"note\":\"Ranked across 10 candidate use cases in the three-week Curve scan.\"},{\"value\":\"189\",\"label\":\"hours\u002Fmonth modeled capacity opportunity\",\"note\":\"Modeled monthly capacity across reporting, research and intake work.\"},{\"value\":\"10\",\"label\":\"ranked AI use cases\",\"note\":\"Every use case scored for value, feasibility and adoption.\"},{\"value\":\"3 wks\",\"label\":\"from kickoff to decision pack\",\"note\":\"From kickoff to a decision-ready, costed plan.\"}]","Potential value was modeled from discovery inputs and agreed assumptions. Actual results depend on implementation, adoption and operating conditions.","Featured client result","Curve was already experimenting with AI. The challenge was deciding what to build, how to sequence the work and where the economics justified investment. A three-week AI Business Scan created a decision-ready view of the opportunity — and the architecture to scale it.","How Curve turned AI ambition into a quantified roadmap.",[100,101],"phases",{":ink":39,":phases":102,"eyebrow":103,"index":104,"lead":105,"title":106},"[{\"tag\":\"One-time · fixed fee\",\"title\":\"AI OS Foundation\",\"items\":[\"Agreed integrations and connections\",\"The first agentic workflow live\",\"Baseline recorded: time, cost, error levels\",\"Shared context and governance configured\"]},{\"tag\":\"Ongoing · agreed scope\",\"title\":\"Shark AI Control Plane\",\"items\":[\"Platform access and maintenance\",\"Monitoring\",\"evaluation and reporting\",\"Versions, updates and rollback\",\"Named owners and support path\"]},{\"tag\":\"Optional · scoped separately\",\"title\":\"Managed AI Operations & new workflows\",\"items\":[\"Run, measure and improve company AI\",\"New agentic workflows added in sequence\",\"Each scoped, priced and prioritized separately\",\"Adoption support and enablement\"]}]","How implementation runs","09","A low-risk path: a one-time foundation, then an ongoing engagement that grows your AI OS. Scope, fees and usage costs are agreed after the diagnostic.","You own the company-specific assets. We maintain the platform.",[108,109],"faq",{":items":110,"eyebrow":111,"index":112,"title":113},"[{\"q\":\"Is a Company AI OS a product we buy off the shelf?\",\"a\":\"No. It is a tailored operating foundation built around your business processes, current tools, data boundaries and roadmap.\"},{\"q\":\"Does it replace our existing software?\",\"a\":\"Usually not. Its role is to connect and improve the systems your team already uses. Any recommended replacement should have a clear business and technical rationale.\"},{\"q\":\"Do we need multiple AI agents before starting?\",\"a\":\"No, but this route is best when the company has validated AI value and expects to scale across several workflows or teams.\"},{\"q\":\"Who owns what?\",\"a\":\"You own your data, company context, organizational memory, client-specific workflows, business rules and evaluation datasets. Shark AI owns and maintains the shared platform: the core, orchestration framework, generic connectors and management interface.\"},{\"q\":\"How is access to sensitive information controlled?\",\"a\":\"The architecture is designed around approved data sources, role-based access, authentication, human approval points and appropriate logging. Exact controls depend on the systems and risks identified during the diagnostic.\"},{\"q\":\"How do we know it is working?\",\"a\":\"Baselines are recorded before the build: time, cost and error levels. From month one you get monthly reporting by workflow — quality, correction rates, cost per task and business KPIs against those baselines.\"}]","FAQ","10","Common questions.",[115,116],"cta-band",{":channels":39,"lead":117,"micro":118,"title":119},"Most engagements start with a short, fixed-fee diagnostic. A 30-minute call is enough to see whether the AI OS route fits your company.","Not ready for the full OS? Start with a Business Scan.","Turn isolated AI wins into a company-wide capability.",[121,122],"takeaways",{":items":123,"title":124},"[\"\u003Cstrong>Not sure where AI pays off yet?\u003C\u002Fstrong> Start with the \u003Ca href=\\\"\u002Fen\u002Fservices\u002Fbusiness-ai-accelerator\\\">Business AI Accelerator\u003C\u002Fa> — the Business Scan is the natural first step into the AI OS.\",\"\u003Cstrong>Founder still building AI confidence?\u003C\u002Fstrong> The \u003Ca href=\\\"\u002Fen\u002Fservices\u002Ffounder-ai-accelerator\\\">Founder AI Accelerator\u003C\u002Fa> builds it one-on-one, with a personal assistant on your own server.\",\"\u003Cstrong>Want to see the agents first?\u003C\u002Fstrong> Browse the \u003Ca href=\\\"\u002Fen\u002Fagents\\\">AI Agents Library\u003C\u002Fa> — eight production agents, each with metrics and a workflow diagram.\"]","Where to go next.",{"title":126,"searchDepth":127,"depth":127,"links":128},"",2,[],"One AI platform for your team, knowledge and agentic workflows — connect, execute, observe, learn, improve, scale.","md",{},true,null,"\u002Fen\u002Fservices\u002Fcompany-ai-os",{"title":5,"description":129},"en\u002Fservices\u002Fcompany-ai-os","VJ1aGNIk7sQAYL6djVaSnI5ShqrDOC8S1dDGebA-F8M",1791363839834]